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The main responsibility includes supporting research operations for our entire institute, mostly using the Python data science stack (e.g. Pandas) and SQL. You will be expected to work with our research and data science team on a variety of tasks, from maintaining and expanding our ETL pipeline, written in Python and Pandas, to querying our Epic Clarity data warehouse, to conducting routine statistical analysis.
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Data Science Analyst (Lead) | 8-11 Years | Data Science - Python, Data Modeling. AWS Data Engineer (Lead) with skills AWS - EKS, AWS - CloudFormation, AWS-Apps, AWS-Infra, AWS DBA, Python, Apache Hive, SQL for location Middle East.
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Masters Degree in bioinformatics, computational biology, data science, data engineering, or other applied science with 3+ years of relevant work experience. Bachelors Degree in bioinformatics, computational biology, data science, data engineering, or other applied science with 5+ years of relevant work experience.
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Extensive experience in solving scientific problems using programming languages relevant to data analysis such as Python, R, Bash (shell scripting), etc. The successful candidate will be responsible for supporting the data, tools and infrastructure that are critical for enabling clinical research objectives that will inform and accelerate the discovery and development of our next generation obesity therapeutics.
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Knowledge and understanding of the National System for GEOINT (NSG) and Intelligence Community; knowledge of private sector data science/analytics, machine learning, and data visualization communities.
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We do everything from data collection to UI/UX development and advanced deep learning, using a broad toolset including Python, C#, and ArcGIS. Our projects include cutting-edge R&D efforts, as well as large mission programs incorporating data processing/optimization, data dissemination techniques, visualization, and collaboration across the commercial and government sectors.
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At least 4 years of experience programming with R or Python in the Data Science field in a professional capacity is required. Master's degree from an accredited university in fields such as outcomes research, epidemiology, biostatistics, data science, predictive analytics with 3 years relevant work experience is required; a doctoral degree (PhD, DrPH, ScD) is preferred.
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3+ years of experience with the Python data science stack (e.g., numpy, pandas, matplotlib, sklearn, etc.) 5+ years of experience with the Python data science stack (e.g., numpy, pandas, matplotlib, sklearn, etc.
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PhD in a field relevant to biomedical research (bioinformatics, biomedical engineering), or computer science (computer science, machine learning, artificial intelligence) or similar. Demonstrated fluency and competency with statistical programming with the R programming language or the Python programming language.
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LLM, RAG, Data engineer, Python, Pyspark, Machine learning, Gen AI, AI/ML, Vector database, Databricks, Snowflake, Education: Bachelor’s degree in engineering, Computer Science or a related field; Master’s degree is a plus.
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Minimum 3 years practical experience and ability to implement data science pipelines and applications in a general programming language such as Python. As a Data Engineer, you will use Python, SQL, Snowflake, dbt and other tools to build automated processes, models and solutions for data operations across the company.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. 5+ years of experience using AI/ML , data science software (e.g., Python-based tools.
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Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Bachelor’s Degree in related field (e.g. Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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You will rely on Python and its data science ecosystem, using various NLP methods, to rigorously measure our product quality, improve enterprise products, and understand the behavior of end-users.
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